AIChE Journal,
Journal Year:
2024,
Volume and Issue:
71(3)
Published: Nov. 26, 2024
Abstract
Biomass
gasification
for
syngas
production
is
a
key
operating
unit
in
the
biomass
utilization
process.
However,
its
overall
efficiency
and
stability
are
often
restricted
by
presence
of
complex
impurities,
including
particulate
matters
(PMs)
tars.
In
this
study,
highly
integrated
ceramic
membrane‐based
reactor
was
developed
high‐temperature
cleaning,
enabling
efficient
situ
removal
PMs
tars
from
bio‐vapors
produced
gasification.
Specifically,
silicon
carbide
(SiC)
membrane
could
separate
volatiles
,
while
structured
Ni
15
La
5
/S1‐SiC
catalyst
(nickel
lanthanum‐laden
silicalite‐1
zeolite
supported
on
SiC
foam)
facilitated
catalytic
reforming
Compared
to
other
control
reactors
(i.e.,
those
containing
either
or
alone),
showed
synergistic
intensification
producing
clean
gasification,
achieving
PM
tar
efficiencies
up
~97%
~90%,
exhibited
excellent
five‐cycle
evaluations
at
800°C.
Modeling
the
fluidization
behavior
of
sand–plastic
mixtures
containing
nonspherical
particles
is
significant
for
designing,
optimizing,
and
scaling
up
biomass/plastic
fluidized
bed
reactors.
However,
large
particle
number
shape
are
challenging
in
DEM-CFD
simulations.
This
study
developed
a
coarse-grained
SuperDEM-CFD
method
that
lumps
spherical
or
into
parcels
to
save
computational
costs.
To
validate
method,
binary
experiments
with
varying
cylinder
mass
fractions
0,
5.4,
18.0%
were
carried
out
bed,
including
pressure
drops,
expansion
height,
orientation
distributions.
The
machine
learning-aided
image
processing
was
employed
analyze
bubble
properties.
Compared
experimental
results,
can
successfully
predict
behavior,
expanded
height.
predicted
distributions,
properties
size
circularity
also
agree
well
experiments,
demonstrating
ability
effectivity
novel
simulate
particles.
Particuology,
Journal Year:
2024,
Volume and Issue:
93, P. 316 - 327
Published: July 14, 2024
We
treat
the
accurate
simulation
of
calcination
reaction
in
particles,
where
particles
are
large
and,
thus,
inner-particle
processes
must
be
resolved.
Because
these
need
to
described
with
coupled
partial
differential
equations
(PDEs)
that
solved
numerically,
computation
times
for
a
single
particle
too
high
use
simulations
involve
many
particles.
Simulations
this
type
arise
when
Discrete
Element
Method
(DEM)
is
combined
Computational
Fluid
Dynamics
(CFD)
investigate
industrial
systems
such
as
quicklime
production
lime
shaft
kilns.
show
that,
based
on
proper
orthogonal
decomposition
and
Galerkin
projection,
reduced
models
can
derived
provide
same
spatial
temporal
resolution
original
PDE
at
considerably
computational
cost.
Replacing
finite
volume
results
an
overall
reduction
reactor
time
by
about
40%
sample
system
treated
here.
Fluids,
Journal Year:
2024,
Volume and Issue:
9(12), P. 301 - 301
Published: Dec. 17, 2024
This
study
investigated
the
fast
pyrolysis
of
biomass
in
fluidized-bed
reactors
using
computational
fluid
dynamics
(CFD)
with
an
Eulerian
multifluid
approach.
A
detailed
analysis
was
conducted
on
influence
various
modeling
parameters,
including
hydrodynamic
models,
heat
transfer
correlations,
and
chemical
kinetics,
product
yield.
The
simulation
framework
integrated
2D
3D
geometrical
setups,
numerical
experiments
performed
OpenFOAM
v11
ANSYS
Fluent
v18.1
for
cross-validation.
While
yield
predictions
exhibited
limited
sensitivity
to
drag
thermal
models
(with
differences
less
than
3%
across
configurations
codes),
results
underline
paramount
role
kinetics
determining
distribution
bio-oil
(TAR),
biochar
(CHAR),
syngas
(GAS).
Simplified
kinetic
schemes
consistently
underestimated
TAR
yields
by
up
20%
overestimated
CHAR
GAS
compared
experimental
data
(which
is
shown
different
compositions
operating
conditions)
can
be
significantly
improved
redefining
reaction
scheme.
Refined
parameters
within
5%
values
while
reducing
discrepancies
outputs.
These
findings
underscore
necessity
precise
enhance
predictive
accuracy
simulations.
